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This formula's way of introducing frequency-dependent noise cannot describe all continuous-time noise processes. For example, consider a noise process consisting of adding a random wave whose amplitude is 1 or −1 at any point in time, and a channel that adds such a wave to the source signal. Such a wave's frequency components are highly ...
Channel capacity, in electrical engineering, computer science, and information theory, is the theoretical maximum rate at which information can be reliably transmitted over a communication channel.
The maximum user signaling rate, synonymous to gross bit rate or data signaling rate, is the maximum rate, in bits per second, at which binary information can be transferred in a given direction between users over the communications system facilities dedicated to a particular information transfer transaction, under conditions of continuous transmission and no overhead information.
The ISQ symbols for the bit and byte are bit and B, respectively.In the context of data-rate units, one byte consists of 8 bits, and is synonymous with the unit octet.The abbreviation bps is often used to mean bit/s, so that when a 1 Mbps connection is advertised, it usually means that the maximum achievable bandwidth is 1 Mbit/s (one million bits per second), which is 0.125 MB/s (megabyte per ...
Stated by Claude Shannon in 1948, the theorem describes the maximum possible efficiency of error-correcting methods versus levels of noise interference and data corruption. Shannon's theorem has wide-ranging applications in both communications and data storage. This theorem is of foundational importance to the modern field of information theory ...
The physical layer net bitrate, [12] information rate, [6] useful bit rate, [13] payload rate, [14] net data transfer rate, [9] coded transmission rate, [7] effective data rate [7] or wire speed (informal language) of a digital communication channel is the capacity excluding the physical layer protocol overhead, for example time division ...
The entropy rate of a data source is the average number of bits per symbol needed to encode it. Shannon's experiments with human predictors show an information rate between 0.6 and 1.3 bits per character in English; [21] the PPM compression algorithm can achieve a compression ratio of 1.5 bits per character in English text.
Most of the listed rates are theoretical maximum throughput measures; in practice, the actual effective throughput is almost inevitably lower in proportion to the load from other devices (network/bus contention), physical or temporal distances, and other overhead in data link layer protocols etc. The maximum goodput (for example, the file ...